Geopolitical crises, raw material shortages, increasing cost of energy and ESG regulations are just some of the challenges, manufacturers around the globe are facing nowadays. The use of smart factory technologies can help mitigate some of these challenges – and beyond that, even create a significant benefit. What these technologies are and what it needs to make them work, that is what we want to talk about with our guest today. Ingo Hecht leads the Application Marketing for Industrial Automation at Infineon. His role includes the close cooperation with our development teams to create new semiconductor solutions enabling the smart factory of today – and tomorrow. 

Guest: Ingo Hecht, Director Application Marketing, Infineon
Moderator: Thomas Reinhardt, Director Corporate Campaigns ＆ Customer Communication, Infineon

Date of publication: 13 December 2023

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„If I had to describe a smart factory, very briefly, I would say: A smart factory captures data at any step of product origination, from raw material to finished good and processes and analyzes this information to intelligently control manufacturing workflow.”

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Moderator:

Hi everyone. Welcome to a new episode of the #MakeIoTwork podcast. My name is Thomas Reinhardt, I am your host, and I am excited to have the opportunity sharing this podcast with all of you.

Geopolitical crises, raw material shortages, increasing cost of energy and ESG regulations are just some of the challenges, manufacturers around the globe are facing nowadays. The use of smart factory technologies can help mitigate some of these challenges – and beyond that, even create a significant benefit. What these technologies are and what it needs to make them work, that is what I want to talk about with my guest today - Ingo Hecht. Ingo leads the Application Marketing for Industrial Automation at Infineon. His role includes the close cooperation with our development teams to create new semiconductor solutions enabling the smart factory of today – and tomorrow. Ingo, thank you for taking the time to talk with me about IIoT, Industry 4.0 and the smart factory.

Ingo Hecht:

Thanks, Thomas. The pleasure is all mine. I look forward to the exchange.

Moderator:

Then let’s start right away with the first question: Given the current challenges, IIoT or Industry 4.0 is a development hotspot at the moment and it will remain a focus topic over the coming years. Can we currently identify any particular trends from the wealth of topics that can be assigned to IIoT?

Ingo Hecht:

In fact, IIoT is a broad field of industrial innovation that has gained momentum in the manufacturing industry, and there are some really significant, future-changing developments currently emerging.

• Artificial Intelligence is a key driver for innovation. The goal is to further optimize various manufacturing processes through targeted machine learning in order to be able to produce even more time- and cost-efficiently at a minimum of resource spending. Intensive model training and a huge data base along usage of artificial neural networks for deep learning allow e.g. the optimization of machine vision in process industries or of predictive maintenance tasks.
• Another example is the improvements in sensor technology. IIoT is very much related to data exchange across any data network and making decisions on it. With the ability of processing more data in shorter time, advanced parameter acquisition such as of temperature, shape, pressure, current or motion is increasingly playing an important role in the development of sensors.
• Of course, energy efficiency at manufacturing lines and its control also plays an important role. Industrial companies are increasingly investing in energy-efficient and thus cost-saving technology - also in the field of robotics. Industry4.0 and its intelligent data processing may optimize the operation of machinery and robots by reducing standby times and maximizing utilization along matched supply chain.

Of course, these are just some examples - but I could go on and on with the list of trends.

Moderator:

Very exciting developments, aren't they? But now let's take a brief look at the smart factory in general: What makes a smart factory possible? What is behind it?

Ingo Hecht:

If I had to describe a smart factory, very briefly, I would say: A smart factory captures data at any step of product origination, from raw material to finished good and processes and analyzes this information to intelligently control manufacturing workflow.

To make this possible, advanced technologies in the area of sensors, secured network connectivity and data processing are needed.

• Sensors capture environmental and product information and convert it into digital data.
• For a fast exchange of this data in between smart factory’s shop floor, control level, edge and cloud wired or wireless connectivity is a prerequisite. As soon as the connection to the communication infrastructure outside the smart factory is used, the issue of data security comes into play. Protecting sensitive data and intellectual property or defeating hacker attacks makes a factory not only “smart” but also secured. After all, data processing in the cloud offers the advantage of high-performance computing capacity - but it has to be secured.
• Sometimes, however, a transfer to the cloud is not necessary. Namely, when data processing takes place at the edge. Processing at the edge provides advantage with being close to the shop floor matching real time requirements and data integrity.

Of course, there’s more such as computing capabilities, but from my point of view, sensors, connectivity and robust security are key capabilities every smart factory has to include as fundament.

Moderator:

So, if I understood you correctly, a smart factory is based on data. Data is at the heart of the smart factory. And to obtain it, we need sensors. Now there is a wide range of sensors: magnetic sensors, current sensors, pressure sensors, radar sensors, and many more. Which of these are relevant for a smart factory?

Ingo Hecht:

Right, we use data to create the necessary transparency for Industry 4.0 applications. They are necessary to control processes. And there are a variety of sensors. With our XENSIV™ family we developed a range of products to meet today’s sensing challenges also in industrial applications. It is one of the broadest portfolios of sensor types on the market, giving customers the widest selection of ready-to-use solutions offering fast time-to-market. For use in smart factories, I would highlight the following in particular: Radar and ToF, MEMS, current sensors, and magnetic sensors. They help to detect status of equipment, power consumption or position of device or material to be manufactured.

Moderator:

But now it's not only important to collect this data, you also have to do something with all the information.

Ingo Hecht:

That's right, information also have to be processed, evaluated and feedbacked to the shop floor based on having made decisions or predictions. But first of all, data have to be transferred via communication busses. Today, the communication landscape in factories is very much fragmented, classic fieldbus protocols coexist with advanced industrial ethernet based solutions. Still today wiring is state of the art.  Reasons are mainly reliability, robustness and low latency requirements. But with latest WiFi6 and 5G standard, this may change within the coming years.

Moderator:

Okay. So, we now have data from different shop floor devices, which we can seamlessly connect and transfer through out the Smart Factory. What is next. How can we create value?

Ingo Hecht:

That is a very good question because in the end, all these technological trends contribute in creating value. And here it is important to think of hardware – such as the sensors we talked about – and software as an integrated unit.

Maybe let’s take Infineon’s latest acquisition of the Swedish start-up Imagimob as an example - a leading platform provider for Machine Learning solutions for edge devices. Combining Infineon’s products and the ModusToolbox™ ML tool with Imagimob’s platform and its expertise in Tiny ML we can make it possible to execute Machine Learning models on small microcontrollers. As a result, Machine Learning algorithms can be processed locally on embedded devices.

It can be applied in a large number of applications which require data processing and decision-making in real time, without being dependent on a cloud or internet connection. For example, in smart factories in the field of predictive maintenance. Customers can monitor the machine state, detect machine anomalies and act in milliseconds, on device. This is how we create value: through high-quality products, complemented by a large ecosystem of software, tools, services and partners – and our experts.

Moderator:

That is a great example. However - edge processing aside - whenever I think about collecting and transferring data, I always think of cyber-attacks and unallowed access to sensitive information. If the virtual doors of smart factories are not properly protected, they can potentially easily be unlocked by attackers - with consequences like unplanned downtime due to operational disruptions, or theft of intellectual property (IP), company know-how or customer information. What can we do to help customers secure their data streams?

Ingo Hecht:

We definitely need the right level of security for the Fourth Industrial Revolution. Years ahead of us will continuously be facing an increased hunger for data and its transmission across all level of a smart factory. This requires a stringent data encryption to avoid misuse of proprietary data and to allow new business models to emerge based on data utilization.  

At Infineon, we aim to optimally support and to give customers peace of mind. Our OPTIGA™ family of security solutions is designed for easy integration into embedded systems to protect the confidentiality, integrity and authenticity of information and devices of a smart factory. It ranges from basic authentication chips to sophisticated implementations, such as OPTIGA™ TPM, which is complying with Trusted Computing Group (TCG) standards.

Moderator:

So, we do not only make the IIoT work with right sensor and connectivity solutions but also with robust security. That’s great. Well, and unfortunately, it's that time again. We have reached the last question. I always ask our guests to take a look into the crystal ball. At the beginning, you mentioned some exciting trends that show the direction in which we are moving in the IIoT. But what would you say are the exciting developments that we can look at in concrete terms?

Ingo Hecht:

In general, the most important topics of digitization will also further advance the smart factory. In addition, in terms of sustainability, it is also a matter of managing a factory in a resource-conserving manner. Greener, more flexible, more efficient and more intelligent thanks to digitization, so to speak.

Exciting examples may be found already right in the framework of predictive maintenance with respect to semiconductors being deployed - I have already given you an example of the possibilities offered by Imagimob.: Now, semiconductor supplier’s physic-based hybrid models derive digital twins of the equipment in the cloud which represent its dynamic behavior and interactions. Fed with the sensor data, historic and real time ones, these models may be trained and output may serve as decision making for reducing power consumption at the factory floor, optimize performance or indicate urgent maintenance ahead.

This is not crystal ball looking, but in realization already today. You can imagine that with the dynamics of AI further advancement may get factories increasingly smarter in shorter time periods.

Moderator:

Thank you very much, Ingo, for your exciting insights.

This brings us to the end of this episode. Dear listeners: If you want to learn more about us and our world of IoT, visit our website www.infineon.io. If you're currently listening to us on Spotify or Apple Podcast, we'd love for you to subscribe to our podcast and leave a little review. Now it only remains for me to wish you a good time. Take care and see you next time.